SparkR (version 2.4.6)

withColumn: WithColumn

Description

Return a new SparkDataFrame by adding a column or replacing the existing column that has the same name.

Usage

withColumn(x, colName, col)
# S4 method for SparkDataFrame,character
withColumn(x, colName, col)

Arguments

x

a SparkDataFrame.

colName

a column name.

col

a Column expression (which must refer only to this SparkDataFrame), or an atomic vector in the length of 1 as literal value.

Value

A SparkDataFrame with the new column added or the existing column replaced.

See Also

rename mutate subset

Other SparkDataFrame functions: SparkDataFrame-class, agg(), alias(), arrange(), as.data.frame(), attach,SparkDataFrame-method, broadcast(), cache(), checkpoint(), coalesce(), collect(), colnames(), coltypes(), createOrReplaceTempView(), crossJoin(), cube(), dapplyCollect(), dapply(), describe(), dim(), distinct(), dropDuplicates(), dropna(), drop(), dtypes(), exceptAll(), except(), explain(), filter(), first(), gapplyCollect(), gapply(), getNumPartitions(), group_by(), head(), hint(), histogram(), insertInto(), intersectAll(), intersect(), isLocal(), isStreaming(), join(), limit(), localCheckpoint(), merge(), mutate(), ncol(), nrow(), persist(), printSchema(), randomSplit(), rbind(), rename(), repartitionByRange(), repartition(), rollup(), sample(), saveAsTable(), schema(), selectExpr(), select(), showDF(), show(), storageLevel(), str(), subset(), summary(), take(), toJSON(), unionByName(), union(), unpersist(), withWatermark(), with(), write.df(), write.jdbc(), write.json(), write.orc(), write.parquet(), write.stream(), write.text()

Examples

# NOT RUN {
sparkR.session()
path <- "path/to/file.json"
df <- read.json(path)
newDF <- withColumn(df, "newCol", df$col1 * 5)
# Replace an existing column
newDF2 <- withColumn(newDF, "newCol", newDF$col1)
newDF3 <- withColumn(newDF, "newCol", 42)
# Use extract operator to set an existing or new column
df[["age"]] <- 23
df[[2]] <- df$col1
df[[2]] <- NULL # drop column
# }